Abstract:
The agriculture sector plays an essential role in a country’s development. This is a primary source
through which the human’s basic needs are fulfilled. Getting the maximum output of agricultural
land is a challenge for professionals. By utilizing agricultural land resources effectively, the
revenue is increased. This research aims to develop a mathematical model for sustainable
production considering economic, environmental, and social factors under uncertainty. Addressing
crop rotation in different areas is more critical to acquiring the fundamental goals and objectives
by optimizing crop selection and land allocation optimally. Optimal results are computed by a
mathematical programming model using MATLAB that deals with multi-objectives for multi products under uncertain circumstances and ensure the high utilization of resources, fulfills
national food security, provides sustainable production techniques, and creates job opportunities
with human health safety. The Augmented Epsilon Constraint Method with lexicographic
optimization has dealt with conflicting multi-objectives (including Profit, Job opportunities, and
yield). The proposed model was validated with primary data from the farmers in the Peshawar
district of Pakistan. The land is classified based on land types such as rainfed, irrigated, etc. This
study compares the single cropping pattern with intercropping, considering the three objectives.
Three crops, ladyfinger, tomato, and round gourd were selected along with their intercropping
combinations. The result shows that intercropping of ladyfinger with a round gourd gives a high
profit and yield, whereas the intercropping of tomato with ladyfinger creates more jobs. Labor is
the leading crop-farming resource, contributing 53% to the total cost. The proposed approach of
crop selection and land allocation with intercropping shows an increase in total revenue, job
opportunities, and yield compared to the traditional approach that has been practiced for the last
decade.
